Non-Alcoholic Fatty Liver Disease in Lean and Non-Obese Individuals: Current and Future Challenges.
Mohammad Shafi KuchayJosé Ignacio Martínez-MontoroNarendra Singh ChoudharyJosé Carlos Fernández-GarcíaBruno Ramos-MolinaPublished in: Biomedicines (2021)
Non-alcoholic fatty liver disease (NAFLD), which approximately affects a quarter of the world's population, has become a major public health concern. Although usually associated with excess body weight, it may also affect normal-weight individuals, a condition termed as lean/non-obese NAFLD. The prevalence of lean/non-obese NAFLD is around 20% within the NAFLD population, and 5% within the general population. Recent data suggest that individuals with lean NAFLD, despite the absence of obesity, exhibit similar cardiovascular- and cancer-related mortality compared to obese NAFLD individuals and increased all-cause mortality risk. Lean and obese NAFLD individuals share several metabolic abnormalities, but present dissimilarities in genetic predisposition, body composition, gut microbiota, and susceptibility to environmental factors. Current treatment of lean NAFLD is aimed at improving overall fitness and decreasing visceral adiposity, with weight loss strategies being the cornerstone of treatment. Moreover, several drugs including PPAR agonists, SGLT2 inhibitors, or GLP-1 receptor agonists could also be useful in the management of lean NAFLD. Although there has been an increase in research regarding lean NAFLD, there are still more questions than answers. There are several potential drugs for NAFLD therapy, but clinical trials are needed to evaluate their efficacy in lean individuals.
Keyphrases
- weight loss
- bone mineral density
- body composition
- metabolic syndrome
- adipose tissue
- public health
- bariatric surgery
- body weight
- type diabetes
- clinical trial
- insulin resistance
- postmenopausal women
- gastric bypass
- roux en y gastric bypass
- randomized controlled trial
- weight gain
- physical activity
- body mass index
- cardiovascular disease
- risk factors
- genome wide
- coronary artery disease
- big data
- deep learning
- risk assessment
- artificial intelligence
- drug induced
- high fat diet induced